Background: Borrelia infections, especially chronic neuroborreliosis ( NB), may cause considerable diagnostic problems. This diagnosis is based on symptoms and findings in the cerebrospinal fluid but is not always conclusive. Purpose: To evaluate brain magnetic resonance imaging ( MRI) in chronic NB, to compare the findings with healthy controls, and to correlate MRI findings with disease duration. Material and Methods: Sixteen well- characterized patients with chronic NB and 16 matched controls were examined in a 1.5T scanner with a standard head coil. T1- ( with and without gadolinium), T2-, and diffusion- weighted imaging plus fluid- attenuated inversion recovery ( FLAIR) imaging were used. Results: White matter lesions and lesions in the basal ganglia were seen in 12 patients and 10 controls ( no significant difference). Subependymal lesions were detected in patients down to the age of 25 and in the controls down to the age of 43. The number of lesions was correlated to age both in patients ( rho=0.83, P < 0.01) and in controls ( rho=0.61, P < 0.05), but not to the duration of disease. Most lesions were detected with FLAIR, but many also with T2- weighted imaging. Conclusion: A number of MRI findings were detected in patients with chronic NB, although the findings were unspecific when compared with matched controls and did not correlate with disease duration. However, subependymal lesions may constitute a potential finding in chronic NB.

BACKGROUND CONTEXT: The development of muscle fat infiltration (MFI) in the neck muscles is associated with poor functional recovery following whiplash injury. Custom software and time-consuming manual segmentation of magnetic resonance imaging (MRI) is required for quantitative analysis and presents as a barrier for clinical translation. PURPOSE: The purpose of this work was to establish a qualitative MRI measure for MFI and evaluate its ability to differentiate between individuals with severe whiplash-associated disorder (WAD), mild or moderate WAD, and healthy controls. STUDY DESIGN/SETTING: This is a cross-sectional study. PATIENT SAMPLE: Thirty-one subjects with WAD and 31 age-and sex-matched controls were recruited from an ongoing randomized controlled trial. OUTCOME MEASURES: The cervical multifidus was visually identified and segmented into eighths in the axial fat/water images (C4-C7). Muscle fat infiltration was assessed on a visual scale: 0 for no or marginal MFI, 1 for light MFI, and 2 for distinct MFI. The participants with WAD were divided in two groups: mild or moderate and severe based on Neck Disability Index % scores. METHODS: The mean regional MFI was compared between the healthy controls and each of the WAD groups using the Mann-Whitney U test. Receiver operator characteristic (ROC) analyses were carried out to evaluate the validity of the qualitative method. RESULTS: Twenty (65%) patients had mild or moderate disability and 11 (35%) were considered severe. Inter- and intra-rater reliability was excellent when grading was averaged by level or when frequency of grade II was considered. Statistically significant differences (pamp;lt;.05) in regional MFI were particularly notable between the severe WAD group and healthy controls. The ROC curve, based on detection of distinct MFI, showed an area-under-the curve of 0.768 (95% confidence interval 0.59-0.94) for discrimination of WAD participants. CONCLUSIONS: These preliminary results suggest a qualitative MRI measure for MFI is reliable and valid, and may prove useful toward the classification of WAD in radiology practice. (C) 2017 Elsevier Inc. All rights reserved.

Inflammation is one of the hallmarks of carcinogenesis. High mammographic density has been associated with increased risk of breast cancer but the mechanisms behind are poorly understood. We evaluated whether breasts with different mammographic densities exhibited differences in the inflammatory microenvironment.Postmenopausal women attending the mammography-screening program were assessed having extreme dense, n = 20, or entirely fatty breasts (nondense), n = 19, on their regular mammograms. Thereafter, the women were invited for magnetic resonance imaging (MRI), microdialysis for the collection of extracellular molecules in situ and a core tissue biopsy for research purposes. On the MRI, lean tissue fraction (LTF) was calculated for a continuous measurement of breast density. LTF confirmed the selection from the mammograms and gave a continuous measurement of breast density. Microdialysis revealed significantly increased extracellular in vivo levels of IL-6, IL-8, vascular endothelial growth factor, and CCL5 in dense breast tissue as compared with nondense breasts. Moreover, the ratio IL-1Ra/IL-1 was decreased in dense breasts. No differences were found in levels of IL-1, IL-1Ra, CCL2, leptin, adiponectin, or leptin:adiponectin ratio between the two breast tissue types. Significant positive correlations between LTF and the pro-inflammatory cytokines as well as between the cytokines were detected. Stainings of the core biopsies exhibited increased levels of immune cells in dense breast tissue.Our data show that dense breast tissue in postmenopausal women is associated with a pro-inflammatory microenvironment and, if confirmed in a larger cohort, suggests novel targets for prevention therapies for women with dense breast tissue.

Anonymization of medical images is necessary for protecting the identity of the test subjects, and is therefore an essential step in data sharing. However, recent developments in deep learning may raise the bar on the amount of distortion that needs to be applied to guarantee anonymity. To test such possibilities, we have applied the novel CycleGAN unsupervised image-to-image translation framework on sagittal slices of T1 MR images, in order to reconstruct facial features from anonymized data. We applied the CycleGAN framework on both face-blurred and face-removed images. Our results show that face blurring may not provide adequate protection against malicious attempts at identifying the subjects, while face removal provides more robust anonymization, but is still partially reversible.

Clinical applications of electron paramagnetic resonance (EPR) dosimetry systems demand high accuracy causing time consuming analysis. The need for high spatial resolution dose measurements in regions with steep dose gradients demands small sized dosimeters. An optimization of the analysis was therefore needed to limit the time consumption. The aim of this work was to introduce a new smaller lithium formate dosimeter model (diameter reduced from standard diameter 4.5 mm to 3 mm and height from 4.8 mm to 3 mm). To compensate for reduced homogeneity in a batch of the smaller dosimeters, a method for individual sensitivity correction suitable for EPR dosimetry was tested. Sensitivity and repeatability was also tested for a standard EPR resonator and a super high Q (SHQE) one. The aim was also to optimize the performance of the dosimetry system for better efficiency regarding measurement time and precision. A systematic investigation of the relationship between measurement uncertainty and number of readouts per dosimeter was performed. The conclusions drawn from this work were that it is possible to decrease the dosimeter size with maintained measurement precision by using the SHQE resonator and introducing individual calibration factors for dosimeter batches. It was also shown that it is possible reduce the number of readouts per dosimeter without significantly decreasing the accuracy in measurements.

The aim of this work was to develop and test a remote end-to-end audit system using lithium formate EPR dosimeters. Four clinics were included in a pilot study, absorbed doses determined in the PTV agreed with TPS calculated doses within ±5% for 3D-CRT and ±7% (k=1) for IMRT/VMAT dose plans.

Interest in high dose rate (HDR) electronic brachytherapy operating at 50 kV is increasing. For quality assurance it is important to identify dosimetry systems that can measure the absorbed doses in absolute terms which is difficult in this energy region. In this work a comparison is made between two dosimetry systems, EPR lithium formate dosimeters and radiochromic EBT2 film.

Both types of dosimeters were irradiated simultaneously in a PMMA phantom using the Axxent EBS. Absorbed dose to water was determined at distances of 10 mm, 30 mm and 50 mm from the EBS. Results were traceable to different primary standards as regards to absorbed dose to water (EPR) and air kerma (EBT2). Monte Carlo simulations were used in absolute terms as a third estimate of absorbed dose to water.

Agreement within the estimated expanded (k = 2) uncertainties (5% (EPR), 7% (EBT2)) was found between the results at 30 mm and 50 mm from the x-ray source. The same result was obtained in 4 repetitions of irradiation, indicating high precision in the measurements with both systems. At all distances, agreement between EPR and Monte Carlo simulations was shown as was also the case for the film measurements at 30mm and 50mm. At 10mm the geometry for the film measurements caused too large uncertainty in measured values depending on the exact position (within sub-mm distances) of the EBS and the 10 mm film results were exculded from comparison.

This work has demonstrated good performance of the lithium formate EPR dosimetry system in accordance with earlier experiments at higher photon energies (192Ir HDR brachytherapy). It was also highlighted that there might be issues regarding the energy dependence and intrinsic efficiency of the EBT2 film that need to be considered for measurements using low energy sources.

Fruit has since long been advocated as a healthy source of many nutrients, however, the high content of sugars in fruit might be a concern.

Objectives

To study effects of an increased fruit intake compared with similar amount of extra calories from nuts in humans.

Methods

Thirty healthy non-obese participants were randomized to either supplement the diet with fruits or nuts, each at +7 kcal/kg bodyweight/day for two months. Major endpoints were change of hepatic fat content (HFC, by magnetic resonance imaging, MRI), basal metabolic rate (BMR, with indirect calorimetry) and cardiovascular risk markers.

Results

Weight gain was numerically similar in both groups although only statistically significant in the group randomized to nuts (fruit: from 22.15±1.61 kg/m2 to 22.30±1.7 kg/m2, p = 0.24 nuts: from 22.54±2.26 kg/m2 to 22.73±2.28 kg/m2, p = 0.045). On the other hand BMR increased in the nut group only (p = 0.028). Only the nut group reported a net increase of calories (from 2519±721 kcal/day to 2763±595 kcal/day, p = 0.035) according to 3-day food registrations. Despite an almost three-fold reported increased fructose-intake in the fruit group (from 9.1±6.0 gram/day to 25.6±9.6 gram/day, p<0.0001, nuts: from 12.4±5.7 gram/day to 6.5±5.3 gram/day, p = 0.007) there was no change of HFC. The numerical increase in fasting insulin was statistical significant only in the fruit group (from 7.73±3.1 pmol/l to 8.81±2.9 pmol/l, p = 0.018, nuts: from 7.29±2.9 pmol/l to 8.62±3.0 pmol/l, p = 0.14). Levels of vitamin C increased in both groups while α-tocopherol/cholesterol-ratio increased only in the fruit group.

Conclusions

Although BMR increased in the nut-group only this was not linked with differences in weight gain between groups which potentially could be explained by the lack of reported net caloric increase in the fruit group. In healthy non-obese individuals an increased fruit intake seems safe from cardiovascular risk perspective, including measurement of HFC by MRI.

Aims: To evaluate the effect of video information given before cardiovascular magnetic resonance imaging on patient anxiety and to compare patient experiences of cardiovascular magnetic resonance imaging versus myocardial perfusion scintigraphy. To evaluate if additional information has an impact on motion artefacts. Background: Cardiovascular magnetic resonance imaging and myocardial perfusion scintigraphy are technically advanced methods for the evaluation of heart diseases. Although cardiovascular magnetic resonance imaging is considered to be painless, patients may experience anxiety due to the closed environment. Design: A prospective randomized intervention study, not registered. Methods: The sample (n=148) consisted of 97 patients referred for cardiovascular magnetic resonance imaging, randomized to receive either video information in addition to standard text-information (CMR-video/n=49) or standard text-information alone (CMR-standard/n=48). A third group undergoing myocardial perfusion scintigraphy (n=51) was compared with the cardiovascular magnetic resonance imaging-standard group. Anxiety was evaluated before, immediately after the procedure and one week later. Five questionnaires were used: Cardiac Anxiety Questionnaire, State-Trait-Anxiety Inventory, Hospital-Anxiety and Depression-scale, MRI-Fear-Survey-Schedule and the MRI-Anxiety-Questionnaire. Motion artefacts were evaluated by three observers, blinded to the information given. Data were collected between April 2015 and April 2016. The study followed the CONSORT guidelines RESULT: The CMR-video group scored lower (better) than the cardiovascular magnetic resonance imaging-standard group in the factor Relaxation (p=0.039) but not in the factor Anxiety. Anxiety levels were lower during scintigraphic examinations compared to the CMR-standard group (p<0.001). No difference was found regarding motion artefacts between CMR-video and CMR-standard. Conclusion: Patient ability to relax during cardiovascular magnetic resonance imaging increased by adding video information prior the exam, which is important in relation to perceived quality in nursing. No effect was seen on motion artefacts. Relevance To Clinical Practice: Video information prior to examinations can be an easy and time effective method to help patients cooperate in imaging procedures.

Background To assess myocardial perfusion, steady-state free precession cardiac magnetic resonance (SSFP, CMR) was compared with gradient-echo–echo-planar imaging (GRE-EPI) using myocardial perfusion scintigraphy (MPS) as reference. Methods Cardiac magnetic resonance perfusion was recorded in 30 patients with SSFP and in another 30 patients with GRE-EPI. Timing and extent of inflow delay to the myocardium was visually assessed. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated. Myocardial scar was visualized with a phase-sensitive inversion recovery sequence (PSIR). All scar positive segments were considered pathologic. In MPS, stress and rest images were used as in clinical reporting. The CMR contrast wash-in slope was calculated and compared with the stress score from the MPS examination. CMR scar, CMR perfusion and MPS were assessed separately by one expert for each method who was blinded to other aspects of the study. Results Visual assessment of CMR had a sensitivity for the detection of an abnormal MPS at 78% (SSFP) versus 91% (GRE-EPI) and a specificity of 58% (SSFP) versus 84% (GRE-EPI). Kappa statistics for SSFP and MPS was 0·29, for GRE-EPI and MPS 0·72. The ANOVA of CMR perfusion slopes for all segments versus MPS score (four levels based on MPS) had correlation r = 0·64 (SSFP) and r = 0·96 (GRE-EPI). SNR was for normal segments 35·63 ± 11·80 (SSFP) and 17·98 ± 8·31 (GRE-EPI), while CNR was 28·79 ± 10·43 (SSFP) and 13·06 ± 7·61 (GRE-EPI). Conclusion GRE-EPI displayed higher agreement with the MPS results than SSFP despite significantly lower signal intensity, SNR and CNR.

Aim. To develop and validate a new instrument measuring patient anxiety during Magnetic Resonance Imaging examinations, Magnetic Resonance Imaging-Anxiety Questionnaire. Background. Questionnaires measuring patients anxiety during Magnetic Resonance Imaging examinations have been the same as used in a wide range of conditions. To learn about patients experience during examination and to evaluate interventions, a specific questionnaire measuring patient anxiety during Magnetic Resonance Imaging is needed. Design. Psychometric cross-sectional study with test-retest design. Methods. A new questionnaire, Magnetic Resonance Imaging-Anxiety Questionnaire, was designed from patient expressions of anxiety in Magnetic Resonance Imaging-scanners. The sample was recruited between October 2012-October 2014. Factor structure was evaluated with exploratory factor analysis and internal consistency with Cronbachs alpha. Criterion-related validity, known-group validity and test-retest was calculated. Results. Patients referred for Magnetic Resonance Imaging of either the spine or the heart, were invited to participate. The development and validation of Magnetic Resonance Imaging-Anxiety Questionnaire resulted in 15 items consisting of two factors. Cronbachs alpha was found to be high. Magnetic Resonance Imaging-Anxiety Questionnaire correlated higher with instruments measuring anxiety than with depression scales. Known-group validity demonstrated a higher level of anxiety for patients undergoing Magnetic Resonance Imaging scan of the heart than for those examining the spine. Test-retest reliability demonstrated acceptable level for the scale. Conclusion. Magnetic Resonance Imaging-Anxiety Questionnaire bridges a gap among existing questionnaires, making it a simple and useful tool for measuring patient anxiety during Magnetic Resonance Imaging examinations.

Recently, much attention has been given to the development of biofunctionalized nanoparticles with magnetic properties for novel biomedical imaging. Guided, smart, targeting nanoparticulate magnetic resonance imaging (MRI) contrast agents inducing high MRI signal will be valuable tools for future tissue specific imaging and investigation of molecular and cellular events. In this study, we report a new design of functionalized ultrasmall rare earth based nanoparticles to be used as a positive contrast agent in MRI. The relaxivity is compared to commercially available Gd based chelates. The synthesis, PEGylation, and dialysis of small (3−5 nm) gadolinium oxide (DEG-Gd2O3) nanoparticles are presented. The chemical and physical properties of the nanomaterial were investigated with Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, transmission electron microscopy, and dynamic light scattering. Neutrophil activation after exposure to this nanomaterial was studied by means of fluorescence microscopy. The proton relaxation times as a function of dialysis time and functionalization were measured at 1.5 T. A capping procedure introducing stabilizing properties was designed and verified, and the dialysis effects were evaluated. A higher proton relaxivity was obtained for as-synthesized diethylene glycol (DEG)-Gd2O3 nanoparticles compared to commercial Gd-DTPA. A slight decrease of the relaxivity for as-synthesized DEG-Gd2O3 nanoparticles as a function of dialysis time was observed. The results for functionalized nanoparticles showed a considerable relaxivity increase for particles dialyzed extensively with r1 and r2 values approximately 4 times the corresponding values for Gd-DTPA. The microscopy study showed that PEGylated nanoparticles do not activate neutrophils in contrast to uncapped Gd2O3. Finally, the nanoparticles are equipped with Rhodamine to show that our PEGylated nanoparticles are available for further coupling chemistry, and thus prepared for targeting purposes. The long term goal is to design a powerful, directed contrast agent for MRI examinations with specific targeting possibilities and with properties inducing local contrast, that is, an extremely high MR signal at the cellular and molecular level.

Background: Platelet-derived growth factor (PDGF) D has been reported to be active in fibroblasts, and in areas of myocardial infarction. In this longitudinal study we evaluated the association between PDGF-D polymorphism and cardiovascular mortality, and attempted to discover whether specific genotype differences regarding risk could be observed, and if gender differences could be seen. Methods: Four hundred seventy-six elderly community participants were included in this study. All participants underwent a clinical examination, echocardiography, and blood sampling including PDGF-D single nucleotide polymorphism (SNP) analyses of the rs974819 A/A, G/A and G/G SNP. The follow-up time was 6.7 years. Results: No specific genotype of rs974819 demonstrated increased cardiovascular mortality in the total population, however, the male group with genotypes A/A and G/A demonstrated an increased risk that persisted in a multivariate evaluation where adjustments were made for well-known cardiovascular risk factors (2.7 fold compared with the G/G genotype). No corresponding finding was observed in the female group. Conclusion: We report here for the first time that the genotypes G/A or A/A of the SNP rs974819 near PDGF-D exhibited a 2.7 fold increased cardiovascular mortality risk in males. Corresponding increased risk could not be observed in either the total population and thus not in the female group. However, the sample size is was small and the results should be regarded as hypothesis-generating, and thus more research in the field is recommended.

Aims This study aims at validating a software tool for automated segmentation and quantification of the left atrium (LA) from 3D echocardiography. Methods and results The LA segmentation tool uses a dual-chamber model of the left side of the heart to automatically detect and track the atrio-ventricular plane and the LA endocardium in transthoracic 3D echocardiography. The tool was tested in a dataset of 121 ultrasound images from patients with several cardiovascular pathologies (in a multi-centre setting), and the resulting volumes were compared with those assessed manually by experts in a blinded analysis using conventional contouring. Bland-Altman analysis showed good agreement between the automated method and the manual references, with differences (mean +/- 1.96 SD) of 0.5 +/- 5.7 mL for LA minimum volume and -1.6 +/- 9.7 mL for LA maximum volume (comparable to the inter-observer variability of manual tracings). The automated tool required no user interaction in 93% of the recordings, while 4% required a single click and only 2% required contour adjustments, reducing considerably the amount of time and effort required for LA volumetric analysis. Conclusion The automated tool was validated in a multi-centre setting, providing quantification of the LA volume over the cardiac cycle with minimal user interaction. The results of the automated analysis were in agreement with those estimated manually by experts. This study shows that such approach has clinical utility for the assessment of the LA morphology and function, automating and facilitating the time-consuming task of analysing 3D echocardiographic recordings.

New deep brain stimulation (DBS) electrode designs offer operation in voltage and current mode and capability to steer the electric field (EF). The aim of the study was to compare the EF distributions of four DBS leads at equivalent amplitudes (3 V and 3.4 mA). Finite element method (FEM) simulations (n = 38) around cylindrical contacts (leads 3389, 6148) or equivalent contact configurations (leads 6180, SureStim1) were performed using homogeneous and patient-specific (heterogeneous) brain tissue models. Steering effects of 6180 and SureStim1 were compared with symmetric stimulation fields. To make relative comparisons between simulations, an EF isolevel of 0.2 V/mm was chosen based on neuron model simulations (n = 832) applied before EF visualization and comparisons. The simulations show that the EF distribution is largely influenced by the heterogeneity of the tissue, and the operating mode. Equivalent contact configurations result in similar EF distributions. In steering configurations, larger EF volumes were achieved in current mode using equivalent amplitudes. The methodology was demonstrated in a patient-specific simulation around the zona incerta and a “virtual” ventral intermediate nucleus target. In conclusion, lead design differences are enhanced when using patient-specific tissue models and current stimulation mode.

BACKGROUND AND PURPOSE: Brain size is commonly described in relation to ICV, whereby accurate assessment of this quantity is fundamental. Recently, an optimized MR sequence (QRAPMASTER) was developed for simultaneous quantification of T1, T2, and proton density. ICV can be measured automatically within minutes from QRAPMASTER outputs and a dedicated software, SyMRI. Automatic estimations of ICV were evaluated against the manual segmentation. MATERIALS AND METHODS: In 19 healthy subjects, manual segmentation of ICV was performed by 2 neuroradiologists (Obs1, Obs2) by using QBrain software and conventional T2-weighted images. The automatic segmentation from the QRAPMASTER output was performed by using SyMRI. Manual corrections of the automatic segmentation were performed (corrected-automatic) by Obs1 and Obs2, who were blinded from each other. Finally, the repeatability of the automatic method was evaluated in 6 additional healthy subjects, each having 6 repeated QRAPMASTER scans. The time required to measure ICV was recorded. RESULTS: No significant difference was found between reference and automatic (and corrected-automatic) ICV (P greater than .25). The mean difference between the reference and automatic measurement was -4.84 +/- 19.57 mL (or 0.31 +/- 1.35%). Mean differences between the reference and the corrected-automatic measurements were -0.47 +/- 17.95 mL (-0.01 +/- 1.24%) and -1.26 +/- 17.68 mL (-0.06 +/- 1.22%) for Obs1 and Obs2, respectively. The repeatability errors of the automatic and the corrected-automatic method were less than1%. The automatic method required 1 minute 11 seconds (SD = 12 seconds) of processing. Adding manual corrections required another 1 minute 32 seconds (SD = 38 seconds). CONCLUSIONS: Automatic and corrected-automatic quantification of ICV showed good agreement with the reference method. SyMRI software provided a fast and reproducible measure of ICV.

This paper presents new methods for use of dense motion fields for motion compensation of interlaced video. The motion estimation is based on previously decoded field-images. The motion is then temporally predicted and used for motion compensated prediction of the field-image to be coded. The motion estimation algorithm is phase-based and uses two or three field-images to achieve motion estimates with sub-pixel accuracy. To handle non-constant motion and the specific characteristics of the field-image to be coded, the initially predicted image is refined using forward motion compensation, based on block-matching. Tests show that this approach achieves higher PSNR than forward block-based motion estimation, when coding the residual with the same coder. The subjective performance is also better.

This paper presents new methods for use of dense motion fields for motion compensation of interlaced video. The motion is estimated using previously decoded field-images. An initial motion compensated prediction is produced using the assumption that the motion is predictable in time. The motion estimation algorithm is phase-based and uses two or three field-images to achieve motion estimates with sub-pixel accuracy. To handle non-constant motion and the specific characteristics of the field-image to be coded, the initially predicted image is refined using forward motion compensation, based on block-matching. Tests show that this approach achieves higher PSNR than forward block-based motion estimation, when coding the residual with the same coder. The subjective performance is also better.

The problem of signal estimation for sparsely and irregularly sampled signals is dealt with using continuous normalized convolution. Image values on real-valued positions are estimated using integration of signals and certainties over a neighbourhood employing a local model of both the signal and the used discrete filters. The result of the approach is that an output sample close to signals with high certainty is interpolated using a small neighbourhood. An output sample close to signals with low certainty is spatially predicted from signals in a large neighbourhood.

This paper introduce multiple hierarchical motion estimation to achieve motion estimates with high spatial resolution. The approach is based on phase-based motion estimation. Results show that the algorithm deal with the smooth motion ﬁeld of hierarchical motion estimation while keeping the advantages of such an approach.

This paper presents a novel method for performing fast estimation of data samples on a desired output grid from samples on an irregularly sampled grid. The output signal is estimated using integration of signals over a neighbourhood employing a local model of the signal using discrete filters. The strength of the method is demonstrated in motion compensation examples by comparing to traditional techniques.

Disturbed, turbulent-like blood flow promotes chaotic wall shear stress (WSS) environments, impairing essential endothelial functions and increasing the susceptibility and progression of vascular diseases. These flow characteristics are today frequently detected at various anatomical, lesion and intervention-related sites, while their role as a pathological determinant is less understood. To present-day, numerous WSS-based descriptors have been proposed to characterize the spatiotemporal nature of the WSS disturbances, however, without differentiation between physiological laminar oscillations and turbulence-related WSS (tWSS) fluctuations. Also, much attention has been focused on magnetic resonance (MR) WSS estimations, so far with limited success; promoting the need of a near-wall surrogate marker. In this study, a new approach is explored to characterize the tWSS, by taking advantage of the tensor characteristics of the fluctuating WSS correlations, providing both a magnitude and an anisotropy measure of the disturbances. These parameters were studied in two patient-specific coarctation models (sever and mild), using large eddy simulations, and correlated against near-wall reciprocal Reynolds stress parameters. Collectively, results showed distinct regions of differing tWSS characteristics, features which were sensitive to changes in flow conditions. Generally, the post-stenotic tWSS was governed by near axisymmetric fluctuations, findings that where not consistent with conventional WSS disturbance predictors. At the 2-3 mm wall-offset range, a strong linear correlation was found between tWSS magnitude and near-wall turbulence kinetic energy (TKE), in contrast to the anisotropy indices, suggesting that MR-measured TKE can be used to assess elevated tWSS regions while tWSS anisotropy estimates request well-resolved simulation methods. (C) 2019 Elsevier Ltd. All rights reserved.

Turbulence and flow eccentricity can be measured by magnetic resonance imaging (MRI) and may play an important role in the pathogenesis of numerous cardiovascular diseases. In the present study, we propose quantitative techniques to assess turbulent kinetic energy (TKE) and flow eccentricity that could assist in the evaluation and treatment of stenotic severities. These hemodynamic parameters were studied in a pre-treated aortic coarctation (CoA) and after several virtual interventions using computational fluid dynamics (CFD), to demonstrate the effect of different dilatation options on the flow field. Patient-specific geometry and flow conditions were derived from MRI data. The unsteady pulsatile flow was resolved by large eddy simulation (LES) including non-Newtonian blood rheology. Results showed an inverse asymptotic relationship between the total amount of TKE and degree of dilatation of the stenosis, where the pre-stenotic hypoplastic segment may limit the possible improvement by treating the CoA alone. Spatiotem-poral maps of TKE and flow eccentricity could be linked to the characteristics of the post-stenotic jet, showing a versatile response between the CoA dilatations. By including these flow markers into a combined MRI-CFD intervention framework, CoA therapy has not only the possibility to produce predictions via simulation, but can also be validated pre-and immediate post treatment, as well as during follow-up studies.

Wall shear stress (WSS) disturbances are commonly expressed at sites of abnormal flow obstructions and may play an essential role in the pathogenesis of various vascular diseases. In laminar flows these disturbances have recently been assessed by the transverse wall shear stress (transWSS), which accounts for the WSS multidirectionality. Site-specific estimations of WSS disturbances in pulsatile transitional and turbulent type of flows are more challenging due to continuous and unpredictable changes in WSS behavior. In these complex flow settings, the transWSS may serve as a more comprehensive descriptor for assessing WSS disturbances of general nature compared to commonly used parameters. In this study large eddy simulations (LES) were used to investigate the transWSS properties in flows subjected to different pathological turbulent flow conditions, governed by a patient-specific model of an aortic coarctation pre and post balloon angioplasty. Results showed that regions of strong near-wall turbulence were collocated with regions of elevated transWSS and turbulent WSS, while in more transitional-like near-wall flow regions a closer resemblance was found between transWSS and low, and oscillatory WSS. Within the frame of this study, the transWSS parameter demonstrated a more multi-featured picture of WSS disturbances when exposed to different types of flow regimes, characteristics which were not depicted by the other parameters alone. (C) 2016 Published by Elsevier Ltd.

Turbulence and flow eccentricity can be measured by magnetic resonance imaging (MRI) and may play an important role in the pathogenesis of numerous cardiovascular diseases. In the present study, we propose quantitative techniques to assess turbulent kinetic energy (TKE) and flow eccentricity that could assist in the evaluation and treatment of stenotic severities. These hemodynamic parameters were studied in a pre-treated aortic coarctation (CoA) and after several virtual interventions using computational fluid dynamics (CFD), to demonstrate the effect of different dilatation options on the flow field. Patient-specific geometry and flow conditions were derived from MRI data. The unsteady pulsatile flow was resolved by large eddy simulation (LES) including non-Newtonian blood rheology. Results showed an inverse asymptotic relationship between the total amount of TKE and degree of dilatation of the stenosis, where turbulent flow proximal the constriction limits the possible improvement by treating the CoA alone. Spatiotemporal maps of TKE and flow eccentricity could be linked to the characteristics of the jet, where improved flow conditions were favored by an eccentric dilatation of the CoA. By including these flow markers into a combined MRI-CFD intervention framework, CoA therapy has not only the possibility to produce predictions via simulation, but can also be validated pre- and immediate post treatment, as well as during follow-up studies.

Turbulent blood flow is often associated with some sort of cardiovascular disease, e.g. sharp bends and/or sudden constrictions/expansions of the vessel wall. The energy losses associated with the turbulent flow may increase the heart workload in order to maintain cardiac output (CO). In the present study, the amount of turbulent kinetic energy (TKE) developed in the vicinity of an aortic coarctation was estimated pre-intervention and in a variety of post-intervention configurations, using scale-resolved image-based computational fluid dynamics (CFD). TKE can be measured using magnet resonance imaging (MRI) and have also been validated with CFD simulations [1], i.e. a parameter that not only can be quantified using simulations but can also be measured by MRI.

Patient-specific geometry and inlet flow conditions were obtained using contrast-enhanced MR angiography and 2D cine phase-contrast MRI, respectively. The intervention procedure was mimicked using an inflation simulation, where six different geometries were obtained. A scale-resolving turbulence model, large eddy simulation (LES), was utilized to resolve the largest turbulent scales and also to capture the laminar-to-turbulent transition. All cases were simulated using baseline CO and with a 20% CO increase to simulate a possible flow adaption after intervention.

For this patient, results shows a non-linear decay of the total amount of TKE integrated over the cardiac phase as the stenotic cross-sectional area is increased by the intervention. Figure 1 shows the original segmented geometry and two dilated coarctation with corresponding volume rendering of the TKE at peak systole. Due to turbulent transition at a kink upstream the stenosis further dilation of the coarctation tends to restrict the TKE to a plateau, and continued vessel expansion may therefore only induce unnecessary stresses onto the arterial wall.

This patient-specific non-invasive framework has shown the geometrical impact on the TKE estimates. New insight in turbulence development indicates that the studied coarctation can only be improved to a certain extent, where focus should be on the upstream region, if further TKE reduction is motivated. The possibility of including MRI in a combined framework could have great potential for future intervention planning and follow-up studies.

Background: Although it is well known that renal artery stenosis may cause renovascular hypertension, it is unclear how the degree of stenosis should best be measured in morphological images. The aim of this study was to determine which morphological measures from Computed Tomography Angiography (CTA) and Magnetic Resonance Angiography (MRA) are best in predicting whether a renal artery stenosis is hemodynamically significant or not. Methods: Forty-seven patients with hypertension and a clinical suspicion of renovascular hypertension were examined with CTA, MRA, captopril-enhanced renography (CER) and captopril test (Ctest). CTA and MRA images of the renal arteries were analyzed by two readers using interactive vessel segmentation software. The measures included minimum diameter, minimum area, diameter reduction and area reduction. In addition, two radiologists visually judged the diameter reduction without automated segmentation. The results were then compared using limits of agreement and intra-class correlation, and correlated with the results from CER combined with Ctest (which were used as standard of reference) using receiver operating characteristics (ROC) analysis. Results: A total of 68 kidneys had all three investigations (CTA, MRA and CER + Ctest), where 11 kidneys (16.2 %) got a positive result on the CER + Ctest. The greatest area under ROC curve (AUROC) was found for the area reduction on MRA, with a value of 0.91 (95 % confidence interval 0.82-0.99), excluding accessory renal arteries. As comparison, the AUROC for the radiologists visual assessments on CTA and MRA were 0.90 (0.82-0.98) and 0.91 (0.83-0.99) respectively. None of the differences were statistically significant. Conclusions: No significant differences were found between the morphological measures in their ability to predict hemodynamically significant stenosis, but a tendency of MRA having higher AUROC than CTA. There was no significant difference between measurements made by the radiologists and measurements made with fuzzy connectedness segmentation. Further studies are required to definitely identify the optimal measurement approach.

Filter networks are used as a powerful tool used for reducing the image processing time and maintaining high image quality.They are composed of sparse sub-filters whose high sparsity ensures fast image processing.The filter network design is related to solvinga sparse optimization problem where a cardinality constraint bounds above the sparsity level.In the case of sequentially connected sub-filters, which is the simplest network structure of those considered in this paper, a cardinality-constrained multilinear least-squares (MLLS) problem is to be solved. Even when disregarding the cardinality constraint, the MLLS is typically a large-scale problem characterized by a large number of local minimizers, each of which is singular and non-isolated.The cardinality constraint makes the problem even more difficult to solve.

An approach for approximately solving the cardinality-constrained MLLS problem is presented.It is then applied to solving a bi-criteria optimization problem in which both thetime and quality of image processing are optimized. The developed approach is extended to designing filter networks of a more general structure. Its efficiency is demonstrated by designing certain 2D and 3D filter networks. It is also compared with the existing approaches.

The aim of this project is to keep the x-ray exposure of the patient as low as reasonably achievable while improving the diagnostic image quality for the radiologist. The means to achieve these goals is to develop and evaluate an efficient adaptive filtering (denoising/image enhancement) method that fully explores true 4D image acquisition modes.

The proposed prototype system uses a novel filter set having directional filter responses being monomials. The monomial filter concept is used both for estimation of local structure and for the anisotropic adaptive filtering. Initial tests on clinical 4D CT-heart data with ECG-gated exposure has resulted in a significant reduction of the noise level and an increased detail compared to 2D and 3D methods. Another promising feature is that the reconstruction induced streak artifacts which generally occur in low dose CT are remarkably reduced in 4D.

Tensors and tensor fields are commonly used in multidimensional signal processing to represent the local structure of the signal. This paper focuses on the case where the sampling on the original signal is anisotropic, e.g when the resolution of the multidimensional image varies depending on the direction which is common e.g. in medical imaging devices. To obtain a geometrically correct description of the local structure there are mainly two possibilities. To resample the image prior to the computation of the local structure tensor field or to compute the tensor field on the original grid and transform the result to obtain a correct geometry of the local structure. This paper deals with the latter alternative and contains an in depth theoretical analysis establishing the appropriate rules for tensor transformations induced by changes in space-time geometry with emphasis on velocity and motion estimation.

The aim of this medical image science project is to increase patient safety in terms of improved image quality and reduced exposure to ionizing radiation in CT. The means to achieve these goals is to develop and evaluate an efficient adaptive filtering (denoising/image enhancement) method that fully explores true 4D image acquisition modes. Four-dimensional (4D) medical image data are captured as a time sequence of image volumes. During 4D image acquisition, a 3D image of the patient is recorded at regular time intervals. The resulting data will consequently have three spatial dimensions and one temporal dimension. Increasing the dimensionality of the data impose a major increase the computational demands. The initial linear filtering which is the cornerstone in all adaptive image enhancement algorithms increase exponentially with the dimensionality. On the other hand the potential gain in Signal to Noise Ratio (SNR) also increase exponentially with the dimensionality. This means that the same gain in noise reduction that can be attained by performing the adaptive filtering in 3D as opposed to 2D can be expected to occur once more by moving from 3D to 4D. The initial tests on on both synthetic and clinical 4D images has resulted in a significant reduction of the noise level and an increased detail compared to 2D and 3D methods. When tuning the parameters for adaptive filtering is extremely important to attain maximal diagnostic value which not necessarily coincide with an an eye pleasing image for a layman. Although this application focus on CT the resulting adaptive filtering methods will be beneficial for a wide range of 3D/4D medical imaging modalities e.g. shorter acquisition time in MRI and improved elimination of noise in 3D or 4D ultrasound datasets.

Atlas-based segmentation is often used to segment medical image regions. For intensity-normalized data, the quality of these segmentations is highly dependent on the similarity between the atlas and the target under the used registration method. We propose a geodesic registration method for interactive atlas-based segmentation using empirical multi-scale anatomical manifolds. The method utilizes unlabeled images together with the labeled atlases to learn empirical anatomical manifolds. These manifolds are defined on distinct scales and regions and are used to propagate the labeling information from the atlases to the target along anatomical geodesics. The resulting competing segmentations from the different manifolds are then ranked according to an image-based similarity measure. We used image volumes acquired using magnetic resonance imaging from 36 subjects. The performance of the method was evaluated using a liver segmentation task. The result was then compared to the corresponding performance of direct segmentation using Dice Index statistics. The method shows a significant improvement in liver segmentation performance between the proposed method and direct segmentation. Furthermore, the standard deviation in performance decreased significantly. Using competing complementary manifolds defined over a hierarchy of region of interests gives an additional improvement in segmentation performance compared to the single manifold segmentation.

Level set methods are a popular way to solve the image segmentation problem in computer image analysis. A contour is implicitly represented by the zero level of a signed distance function, and evolved according to a motion equation in order to minimize a cost function. This function defines the objective of the segmentation problem and also includes regularization constraints. Gradient descent search is the de facto method used to solve this optimization problem. Basic gradient descent methods, however, are sensitive for local optima and often display slow convergence. Traditionally, the cost functions have been modified to avoid these problems. In this work, we instead propose using a modified gradient descent search based on resilient propagation (Rprop), a method commonly used in the machine learning community. Our results show faster convergence and less sensitivity to local optima, compared to traditional gradient descent.

Level set methods are a popular way to solve the image segmentation problem. The solution contour is found by solving an optimization problem where a cost functional is minimized. Gradient descent methods are often used to solve this optimization problem since they are very easy to implement and applicable to general nonconvex functionals. They are, however, sensitive to local minima and often display slow convergence. Traditionally, cost functionals have been modified to avoid these problems. In this paper, we instead propose using two modified gradient descent methods, one using a momentum term and one based on resilient propagation. These methods are commonly used in the machine learning community. In a series of 2-D/3-D-experiments using real and synthetic data with ground truth, the modifications are shown to reduce the sensitivity for local optima and to increase the convergence rate. The parameter sensitivity is also investigated. The proposed methods are very simple modifications of the basic method, and are directly compatible with any type of level set implementation. Downloadable reference code with examples is available online.

To quantitatively and qualitatively evaluate the water-signal performance of the consistent intensity inhomogeneity correction (CIIC) method to correct for intensity inhomogeneities METHODS: Water-fat volumes were acquired using 1.5 Tesla (T) and 3.0T symmetrically sampled 2-point Dixon three-dimensional MRI. Two datasets: (i) 10 muscle tissue regions of interest (ROIs) from 10 subjects acquired with both 1.5T and 3.0T whole-body MRI. (ii) Seven liver tissue ROIs from 36 patients imaged using 1.5T MRI at six time points after Gd-EOB-DTPA injection. The performance of CIIC was evaluated quantitatively by analyzing its impact on the dispersion and bias of the water image ROI intensities, and qualitatively using side-by-side image comparisons.

This paper compares numerical predictions of turbulence intensity with in vivo measurement. Magnetic resonance imaging (MRI) was carried out on a 60-year-old female with a restenosed aortic coarctation. Time-resolved three-directional phase-contrast (PC) MRI data was acquired to enable turbulence intensity estimation. A contrast-enhanced MR angiography (MRA) and a time-resolved 2D PCMRI measurement were also performed to acquire data needed to perform subsequent image-based computational fluid dynamics (CFD) modeling. A 3D model of the aortic coarctation and surrounding vasculature was constructed from the MRA data, and physiologic boundary conditions were modeled to match 2D PCMRI and pressure pulse measurements. Blood flow velocity data was subsequently obtained by numerical simulation. Turbulent kinetic energy (TKE) was computed from the resulting CFD data. Results indicate relative agreement (error a parts per thousand 10%) between the in vivo measurements and the CFD predictions of TKE. The discrepancies in modeled vs. measured TKE values were within expectations due to modeling and measurement errors.

In this work, we address the challenge of seamlessly visualizing astronomical data exhibiting huge scale differences in distance, size, and resolution. One of the difficulties is accurate, fast, and dynamic positioning and navigation to enable scaling over orders of magnitude, far beyond the precision of floating point arithmetic. To this end we propose a method that utilizes a dynamically assigned frame of reference to provide the highest possible numerical precision for all salient objects in a scene graph. This makes it possible to smoothly navigate and interactively render, for example, surface structures on Mars and the Milky Way simultaneously. Our work is based on an analysis of tracking and quantification of the propagation of precision errors through the computer graphics pipeline using interval arithmetic. Furthermore, we identify sources of precision degradation, leading to incorrect object positions in screen-space and z-fighting. Our proposed method operates without near and far planes while maintaining high depth precision through the use of floating point depth buffers. By providing interoperability with order-independent transparency algorithms, direct volume rendering, and stereoscopy, our approach is well suited for scientific visualization. We provide the mathematical background, a thorough description of the method, and a reference implementation.

MRI is a well known and widely spread technique to characterize cardiac pathologies due to its high spatial resolution, its accessibility and its adjustable contrast among soft tissues.

In attempt to close the gap between blood flow, myocardial movement and the cardiac fucntion, researching in the MRI field addresses the quantification of some of the most relevant blood and myocardial parameters.

During this proyect a new tool that allows reading, postprocessing, quantifying and visualizing 2D motion sense MR data has been developed. In order to analyze intracardiac blood flow and wall motion, the new tool quantifies velocity, turbulent kinetic energy, pressure and strain.

In the results section the final tool is presented, describing the visualization modes, which represent the quantified parameters both individually and combined; and detailing auxiliary tool features as masking, thresholding, zooming, and cursors.

Finally, thecnical aspects as the convenience of two dimensional examinations to create compact tools, and the challenges of masking as part of the relative pressure calculation, among others, are discussed; ending up with the proposal of some future developments.